“Ubiquitous computing” is a concept first introduced by Mark Weiser in 1993. Since then, it has been used as a keyword in various technical and cultural contexts and presented in various forms.
The rapid development of information technology (IT) since the onset of the information age has brought about a ubiquitous era in which a networking service can be provided to users without time and space constraints. In a ubiquitous environment, a service provider must be able to identify a user's needs and surroundings on its own and provide a service, which meets the user's needs, at the right time and without the intervention of the user.
A computing system that applies a computing function to an environment and an object and connects them through a network is an essential infrastructure environment for the implementation of a ubiquitous service.
To build a ubiquitous infrastructure environment in a space by removing space constraints, blocks of space have been created in the form of intelligent spaces.
Intelligent spaces build a close and extensive communication system on a network in order to create an integrated ubiquitous service. However, various elements that form each intelligent space are specific only to a corresponding intelligent space. This is because not all intelligent spaces are designed with the same standards, and infrastructures, devices, etc. introduced into these intelligent spaces are developed with various standards and different levels of technology.
Before creating intelligent spaces, project planners design a detailed project execution process and project deliverables through a planning process. However, due to the above-mentioned characteristics of intelligent spaces, the principle of creating the intelligent spaces changes according to the purpose, scale, and cost of each intelligent space. Accordingly, it is inevitable to modify requirements for creating each intelligent space.
An intelligent space integrates various levels of technology. To create an intelligent space, knowledge about the development of intelligent objects, the principle of space design, the implementation of an intelligent space service, and the like are required. However, it is very difficult to have expertise on such diverse fields. From the perspective of intelligent space design that puts emphasis on purpose and service, it is also not necessary for a project planner to have all the technical knowledge about the construction of these infrastructures.
In the aspect of intelligent space design, a vision algorithm, which is related to a security service such as tracking and surveillance, depends on devices and space more than any other conventional service technologies. Thus, the vision algorithm has a development structure that cannot allow a space designer, a service developer, and a device developer to work independently.
In the aspect of intelligent space development, this unnecessary connection between the space designer, the service developer, and the device developer has been pointed out as a major cause of development efficiency reduction. Due to this connection, research on vision technology and sensor structure placement has mostly been conducted in terms of vision algorithms and in a shortsighted manner or by technology developers, but not by space designers or project planners.
Furthermore, research on image processing of a video surveillance system has mostly focused on the development of hardware with stable and efficient performance and the development of motion- or object-tracking algorithms.
However, camera placement should be considered that involves measuring the total coverage of cameras through camera cooperation and be considered with a higher priority in system design than the performance of hardware and each algorithm. It cannot be verified just with experiments such as a simple algorithm performance evaluation test conducted in a controlled environment.